OUTLINE FOR CHAPTER
14
Analyses of Variance With Repeated Measures
 Introduction
 Similarities and differences between ANOVAs with and without repeated
measures
 Repeated measures and the univariate/multivariate distinction
 The distinction between separate ANOVAs using data from the same
subjects vs. a unified repeated measures ANOVA
 The notion of a "withinsubjects" factor (and three situations
that create this kind of factor)
 OneWay Repeated Measures ANOVAs
 Different labels for this kind of ANOVA
 Purpose
 Presentation of results
 The ANOVA summary table
 Results presented within a passage of text
 Post hoc investigations
 The presentation order of levels of the withinsubjects factor
 Practice effects, fatigue effects, and confounding
 Three ways to alter the order of the factor's levels
 Carryover effects
 The sphericity assumption
 The importance and meaning of the sphericity assumption
 Mauchly's test
 The GeisserGreenhouse conservative Ftest procedure
 The HuynhFeldt correction
 TwoWay Repeated Measures ANOVAs
 Different labels for this kind of ANOVA
 Purpose
 Presentation of results
 The ANOVA summary table
 Results presented within a passage of text
 Post hoc investigations
 The presentation order of levels of the withinsubjects factor
 The sphericity assumption
 Practical versus statistical significance
 TwoWay Mixed ANOVAs
 Labels for this kind of ANOVA
 Data layout and purpose
 The importance of being able to picture a study's factors,
levels, and subjects
 Three research questions: two dealing with main effects and
one with interaction
 Presentation of results
 The ANOVA summary table
 The "upper" and "lower" sections of the summary table
 The presence of two error terms
 Using information from the table
 Results presented within a passage of text
 Post hoc investigations
 Related issues
 The order in which the levels of the withinsubjects factor
are presented
 The sphericity assumption
 The distinction between statistical and practical significance
 Three Final Comments
 What kind of ANOVA was it?
 Practical versus statistical significance
 The possibility of inferential error
